1. Field of the Invention
The present invention relates to gait detection systems, gait detection apparatuses, devices, and gait detection methods.
2. Description of the Related Art
One type of gait detection system includes a so-called pedometer system which employs a built-in pendulum and which detects the motion of the pendulum during walking.
Another gait detection system employs, instead of a pendulum, an acceleration sensor and a gyro sensor to detect motion (movement) on the basis of the acceleration detected by these sensors, whereby the gait of the user can be detected.
The gait of a pedestrian detected by the foregoing methods is used to simply count the steps as in a pedometer and to estimate the distance traveled by the pedestrian on the basis of the detected gait. This is used to provide a so-called autonomous navigation capability in a navigation system using a Global Positioning System (GPS) in which the position determined on the basis of electromagnetic waves transmitted from a GPS satellite is corrected on the basis of the distance traveled by the pedestrian. Hitherto, in such a case, the pedestrian's step length is estimated by utilizing the correlation of the step length with two parameters, namely, the walking frequency, i.e., the number of steps per unit time, and the height.
Another technology for identifying the person or animal being detected on the basis of the detected gait is proposed. In this case, the technology may employ the foregoing systems and a system for detecting the gait by detecting footsteps. For example, a microphone is used to pick up hoofbeats generated when a horse's hooves make contact with the ground, and the horse is identified on the basis of the gait which can be detected from the sound of hoofs (see Japanese Unexamined Patent Application Publication No. 2000-193520).
The foregoing detection systems have the following problems:
In the mechanical system such as the pedometer using the built-in pendulum, even when a pedestrian is not walking, the motion in response to even slight pendulum movement may be counted as one step. Accordingly, the measurement accuracy is reduced.
In both the system using the built-in pendulum and the system using the acceleration sensor and the gyro sensor, a detection device must be placed at a specific location such as the waist of a pedestrian in order to improve the detection accuracy. In the system using the acceleration sensor and the gyro sensor, the device must be placed on the pedestrian, and the axial direction of the sensors must be detected, since the detection results depend on the sensor directions. Such detection is time-consuming, and the program and circuit configurations become complicated. A multi-axial acceleration sensor is necessary to detect the complex gait activity of a pedestrian. As a result, the configuration becomes more complex, and the cost is increased.
When detecting vibrations by the acceleration sensor and the gyro sensor or when detecting the gait on the basis of the sound picked up by the microphone, each step is detected by processing a detected waveform. In this case, a method for simply counting the peaks of waveforms generated during walking may be employed. Another method converts time-series variations in waveforms into a frequency intensity spectrum pattern by subjecting the variations to Fourier transform or wavelet transform. The method analyzes the pattern, thereby detecting the gait.
In an actual environment for detecting the gait, when a pedestrian is in a vehicle, the microphone picks up noise made by the vehicle and extraneous noise other than that made by the pedestrian. In any of the foregoing methods, the detection accuracy or the analysis accuracy is greatly influenced by the noise. In addition, when detecting the gait of a human being, it is impossible to analyze the gait on the basis of the sound picked up by the microphone and to identify the person (pedestrian) because of the extraneous noise pickup.
To say nothing of a case in which the peaks of waveforms are simply counted, when a waveform is subjected to Fourier transform, the information loses its time component. It is thus impossible to accurately detect various gait patterns of a pedestrian, such as trotting, walking upstairs and downstairs, and the like. A waveform is subjected to wavelet transform by presetting the duration required for making one step, extracting a detection waveform by a windowing function having a duration longer than the duration for one step, and performing frequency analysis of the waveform, whereby a frequency spectrum for one step is obtained. This processing is cumbersome. When the duration for making one step is longer than the preset operation duration or windowing function, the processing may become erroneous.
When estimating the distance traveled by a pedestrian on the basis of the gait of the pedestrian, step length is estimated from the pedestrian's gait and height. Known detection systems lack satisfactory detection accuracy in gait detection. When the gait of the pedestrian shows a pattern differing from the normal gait, that is, when the pedestrian walks with long strides, trots, or walks upstairs and/or downstairs, it is difficult to identify who the pedestrian is. It is also difficult to accurately detect the step length and to accurately estimate the distance traveled.
When a device including a wristwatch is provided with a gait detection function, the size may be increased and the configuration may become complex because the foregoing systems require that a pendulum, an acceleration sensor, a gyro sensor, and the like be added to the device.